{
\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}
\begin{tabular}{l*{3}{c}}
\hline\hline
            &\multicolumn{1}{c}{(1)}&\multicolumn{1}{c}{(2)}&\multicolumn{1}{c}{(3)}\\
            &\multicolumn{1}{c}{2014-2019}&\multicolumn{1}{c}{2009-2019}&\multicolumn{1}{c}{2009-2019}\\
\hline
2019 election&      -5.962\sym{***}&      -12.76\sym{***}&      -20.09\sym{***}\\
            &    (0.0621)         &    (0.0675)         &    (0.0745)         \\
[1em]
EP election in 2019&      -0.120\sym{*}  &      -1.107\sym{***}&     -0.0808         \\
            &    (0.0666)         &    (0.0680)         &    (0.0665)         \\
[1em]
Ciutadella in 2019&       1.008         &       0.245         &       0.536         \\
            &     (0.693)         &     (0.589)         &     (0.589)         \\
[1em]
EP 2019 x Ciutadella&      -2.985\sym{***}&      -2.375\sym{***}&      -3.400\sym{***}\\
            &     (0.737)         &     (0.780)         &     (0.780)         \\
[1em]
2014-2015 election&                     &                     &      -14.07\sym{***}\\
            &                     &                     &    (0.0392)         \\
\hline
\(N\)       &      131212         &      215191         &      215191         \\
\hline\hline
\multicolumn{4}{l}{\footnotesize Standard errors in parentheses}\\
\multicolumn{4}{l}{\footnotesize All models include voting station fixed effects}\\
\multicolumn{4}{l}{\footnotesize Standard errors are clustered by voting station}\\
\multicolumn{4}{l}{\footnotesize \sym{*} \(p<0.10\), \sym{**} \(p<0.05\), \sym{***} \(p<0.01\)}\\
\end{tabular}
}
